Keywords: decision support systems, DSS, fuel blends, diesel engines, energy efficiency, IC engines, fish oil biodiesel, ELECTRE, fuzzy AHP, analytical hierarchy process, FAHP, biofuels, MCDM, multicriteria decision making, blend optimisation, blend ranking
Development of decision support system to select the best fuel blend in IC engines to enhance the energy efficiency
This paper describes an application of hybrid MCDM technique for the selection of optimum blend in fish oil biodiesel among the six alternative fuel blends diesel, B20, B40, B60, B80 and B100 which is prepared by varying the amount of diesel with biodiesel. Brake thermal efficiency (BTE), exhaust gas temperature (EGT), oxides of nitrogen (NOx), smoke, hydrocarbon (HC), carbon monoxide (CO), carbon dioxide (CO2), ignition delay (ID), combustion duration (CD) and maximum rate of pressure rise (MRPR) are considered as evaluation criteria. A single cylinder, constant speed and direct injection diesel engine with a rated output of 4.4 kW was used for exploratory analysis of evaluation criteria at different load conditions. The proposed model, fuzzy analytical hierarchy process (FAHP) is integrated with elimination et and choice translating reality (ELECTRE) to evaluate the optimum blend. Here the FAHP is used to determine the relative weights of the criteria, whereas ELECTRE is used for obtaining the final ranking of alternative blends.